Computer Vision Homography In the field of computer
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Computer Vision Homography In the field of computer vision, any two images of the same planar surface in space are related by a homography (assuming a pinhole camera model). 1 From Wikipedia
Computer Vision 8. 7976964 e-01 3. 1245438 e-01 -3. 9430589 e+01 -1. 8389418 e-01 9. 3847198 e-01 1. 5315784 e+02 1. 9641425 e-04 -1. 6015275 e-05 1. 0000000 e+00
Computer Vision Plane Transfer Homography X P P' World x C Hx C' • Because we assume the world is a plane, x and transferred points x’ are related by a homography. • If world plane coordinate is p, then • x=Ap and x’=A’p. • x’ = A’A-1 x. 3
Computer Vision RANSAC for Fundamental Matrix Step 1. Extract features Step 2. Compute a set of potential matches Step 3. do Step 3. 1 select minimal sample (i. e. 7 matches) Step 3. 2 compute solution(s) for F Step 3. 3 determine inliers (verify hypothesis) (generate hypothesis) until a large enough set of the matches become inliers Step 4. Compute F based on all inliers Step 5. Look for additional matches Step 6. Refine F based on all correct matches 4
Computer Vision Example: robust computation from H&Z Interest points (500/image) (640 x 480) Putative correspondences (268) (Best match, SSD<20, ± 320) Outliers (117) (t=1. 25 pixel; 43 iterations) Inliers (151) Final inliers (262) 5
